Concepts & Explanations

Multilayer networks capture systems where entities interact through multiple relationship types at once. This page orients you within the conceptual docs and points to the deeper explanations you may need next.

What’s in this section

• Multilayer Networks 101 — Modeling choices (multiplex, heterogeneous, temporal) and when each makes sense

• The py3plex Core Model — Node-layer pairs, the supra-adjacency matrix, and how py3plex wraps NetworkX

• Design Principles — Why py3plex is structured as it is

• Algorithm Landscape — What analysis tools are available and how they fit together

Pick a path

• New to multilayer networks? Start with Multilayer Networks 101, then read The py3plex Core Model to see how layers, node-layer pairs, and coupling are represented.

• Coming from NetworkX? Jump to The py3plex Core Model for the node-layer abstraction and supra-adjacency matrix, then skim Design Principles for rationale.

• Building expertise? Read in order: theory (Multilayer Networks 101), implementation (The py3plex Core Model), design rationale (Design Principles), and tools (Algorithm Landscape).

After Reading This Section

You’ll be able to:

• Model real-world systems as multilayer networks instead of flattening away layer semantics.

• Choose sensible parameters (e.g., layer definitions, inter-layer coupling strength) for your data.

• Interpret results in terms of layers and node-layer pairs rather than anonymous nodes.

• Avoid common pitfalls (e.g., flattening important structure, mismatched identifiers).

Tip

Quick check: After reading this section, you should be able to answer:

• What distinguishes multiplex from heterogeneous networks?

• What does the supra-adjacency matrix represent and why use it?

• When should you tighten vs. relax inter-layer coupling?

Relation to other sections

• Overview (Overview) — Quick 2-minute intro to multilayer networks.

• How-to Guides (How-to Guides) — Apply these concepts in practice.

• Reference (API & DSL Reference) — Detailed API and algorithm documentation.

• Examples (Examples & Recipes) — See concepts in action with real code.

Jump to practical applications

Once you understand the concepts:

• Load networks: How to Load and Build Networks

• Compute statistics: How to Compute Network Statistics

• Detect communities: How to Run Community Detection on Multilayer Networks

• Query networks: How to Query Multilayer Graphs with the SQL-like DSL